The high-risk model associated with SYTL4 predicts poor prognosis and correlates with immune infiltration in AML

Acute myeloid leukemia (AML) currently lacks a definitive cure. Studies have highlighted the involvement of SYTL4 expression levels in neoplasms, yet its specific roles in AML remain unexplored in the literature. Utilizing the TCGA and XENA databases, this study investigated SYTL4 expression levels in AML and identified associations between SYTL4 overexpression and clinicopathological features, prognosis, and immune infiltration in AML patients through genomic analysis. ROC analysis demonstrated the diagnostic value of SYTL4 overexpression in AML. Kaplan-Meier survival, Cox regression, and Lasso analyses were employed to explore SYTL4-coexpressed long non-coding RNAs linked to AML patient prognosis, alongside the construction of nomograms and risk models. SYTL4 expression was significantly elevated in AML and correlated with FAB classification, cytogenetic risk, IDH1 R140 mutation, and NPM1 mutation in cancer patients. SYTL4 overexpression signaled a poor prognosis, serving as a risk indicator for assessing adverse outcomes in AML patients. SYTL4 expression levels also correlated with AML immune cell levels and markers. COX regression analysis revealed that LINC01700, CPNE8-AS1, HOXA10-AS, LINC00899, and SYTL4 influenced adverse AML prognosis. Patients in the high-risk group for these factors experienced significantly poor outcomes, which were closely associated with aDC, CD8 T cells, and TH17 cells. In summary, SYTL4 overexpression is linked to poor prognosis and immune infiltration in AML, with the constructed risk model intended as a prognostic evaluation tool for AML patients.

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Publication Details

Journal
Biochemistry and Biophysics Reports
Published
2024-11-29
DOI
https://doi.org/10.1016/j.bbrep.2024.101859
Primary Topic
Acute Myeloid Leukemia Research
Type
article
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article

The high-risk model associated with SYTL4 predicts poor prognosis and correlates with immune infiltration in AML

Bohui Peng, Qiang Guo, Dan Li, Ke Shi
Biochemistry and Biophysics Reports
Acute Myeloid Leukemia Research
article

The high-risk model associated with SYTL4 predicts poor prognosis and correlates with immune infiltration in AML

Bohui Peng, Qiang Guo, Dan Li, Ke Shi
article en

Abstract

Acute myeloid leukemia (AML) currently lacks a definitive cure. Studies have highlighted the involvement of SYTL4 expression levels in neoplasms, yet its specific roles in AML remain unexplored in the literature. Utilizing the TCGA and XENA databases, this study investigated SYTL4 expression levels in AML and identified associations between SYTL4 overexpression and clinicopathological features, prognosis, and immune infiltration in AML patients through genomic analysis. ROC analysis demonstrated the diagnostic value of SYTL4 overexpression in AML. Kaplan-Meier survival, Cox regression, and Lasso analyses were employed to explore SYTL4-coexpressed long non-coding RNAs linked to AML patient prognosis, alongside the construction of nomograms and risk models. SYTL4 expression was significantly elevated in AML and correlated with FAB classification, cytogenetic risk, IDH1 R140 mutation, and NPM1 mutation in cancer patients. SYTL4 overexpression signaled a poor prognosis, serving as a risk indicator for assessing adverse outcomes in AML patients. SYTL4 expression levels also correlated with AML immune cell levels and markers. COX regression analysis revealed that LINC01700, CPNE8-AS1, HOXA10-AS, LINC00899, and SYTL4 influenced adverse AML prognosis. Patients in the high-risk group for these factors experienced significantly poor outcomes, which were closely associated with aDC, CD8 T cells, and TH17 cells. In summary, SYTL4 overexpression is linked to poor prognosis and immune infiltration in AML, with the constructed risk model intended as a prognostic evaluation tool for AML patients.

Biochemistry and Biophysics ReportsVol. 41
Hubei University of Medicine (CN), Taihe Hospital (CN), The First People's Hospital of Changde (CN)
No poverty
Openalex Percentile: Top 65%
Acute Myeloid Leukemia Research
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